Application of Attentive Sensing to Distance Learning

Position Title: Research Assistant/summer researcher

Location:  Lassonde 002

Professor: James Elder

Department: Electrical Engineering and Computer Science

Contact for Professor (Email, phone):

# of positions available: 2

Project Description:

Application of Attentive Sensing to Distance Learning.

Video cameras generate massive quantities of data, but using these data effectively requires intelligent software and hardware.  Inspired by the human visual attention and oculomotor systems, our laboratory has invented and patented a series of attentive sensor devices that automatically orients an attentive camera to capture the most important details in a scene.

An important potential application of this technology is distance learning.  One of the challenges is to allow students to communicate effectively with the lecturer.  For example, when a student asks a question, communication will be more effective if the instructor has a zoomed view of the student's face, so that s/he can interpret expressions etc.  By the same token, it can be helpful if the students also have a zoomed view of the professor as she moves around the room.

The goal of this project is to apply attentive sensing technology ( to this problem.  This technology is able to monitor a large environment such as a classroom and direct a high-resolution 'attentive' sensor to events of interest.

More information on the lab can be found at

Duties and Responsibilities of the student:

The student will assist in fine-tuning the sensor to the application and evaluate its performance and will work closely with graduate students, postdoctoral fellows, software engineers and research scientists in the lab, as well as with the Principal Investigator, Professor James Elder.

The student will:

1.         Study the problem of detecting hand-raises in the preattentive sensor stream

2.         Study the problem of tracking the professor in the preattentive sensor stream

3.         Implement algorithms for detecting hand-raises and tracking the professor based upon these investigations

4.         Evaluate these algorithms in a real-classroom setting, using proprietary attentive sensing technology

Skills and Qualifications:

1.       Algorithm design

2.      Programming in C++ and MATLAB

3.      Ability to work in a team

Degrees, courses and Disciplines prerequisite:

EECS students (CS, CE, EE) or students with strong programing and mathematics skills preferred.

Stipend : TBD

Duration: 16 weeks minimum

Start Date: 05/01/2018 (estimated)

End Date: 08/31/2018 (estimated)


If you are interested in this research project, please contact Dr. James Elder at